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[Bugfix] Fix level-2 sleep/wake/reload with enable_lora=True (#39935)

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Signed-off-by: Silen Naihin <silen.naihin@gmail.com>
Co-authored-by: Dakai An <dakaian108@gmail.com>
Co-authored-by: Jiangyun Zhu <riverclouds.zhu@qq.com>
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Silen Naihin
2026-08-06 09:13:10 +08:00
committed by GitHub
co-authored by Dakai An Jiangyun Zhu
parent 8cfa01cdd2
commit b50fdebce0
11 changed files with 252 additions and 4 deletions
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docs/features/sleep_mode.md
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@@ -18,7 +18,7 @@ Key benefits:
## Sleep levels
Level 1 sleep will offload the model weights and discard the KV cache. The content of KV cache is forgotten. Level 1 sleep is good for sleeping and waking up the engine to run the same model again. The model weights are backed up in CPU memory. Please make sure there's enough CPU memory to store the model weights. Level 2 sleep will discard both the model weights and the KV cache (while the model's buffers are kept in CPU, like rope scaling tensors). The content of both the model weights and KV cache is forgotten. Level 2 sleep is good for sleeping and waking up the engine to run a different model or update the model, where previous model weights are not needed, e.g. RLHF weight update.
Level 1 sleep will offload the model weights and discard the KV cache. The content of KV cache is forgotten. Level 1 sleep is good for sleeping and waking up the engine to run the same model again. The model weights are backed up in CPU memory. Please make sure there's enough CPU memory to store the model weights. Level 2 sleep will discard both the model weights and the KV cache (while the model's buffers are kept in CPU, like rope scaling tensors). The content of both the model weights and KV cache is forgotten. Level 2 sleep is good for sleeping and waking up the engine to run a different model or update the model, where previous model weights are not needed, e.g. RLHF weight update. Level 2 sleep is also useful when there is not enough CPU memory to back up the model weights, e.g. when a colocated trainer already uses CPU memory for offloading its own state; since nothing is backed up, restore the weights after waking up with `collective_rpc("reload_weights")`.
## Usage